Anomaly detection is used to identify items, events, or traffic that exhibit behavior that does not conform to an expected pattern or data. Anomaly detection systems may, for example, learn normal activity and take action for behavior that deviates from what is learned as normal behavior. Network data features may be grouped and then serve as input to downstream algorithms used to identify anomalous network behavior.
Corresponding reference characters indicate corresponding parts throughout the several views of the drawings.